Ren, Zhengzheng; Li, Jiaorui; Xu, Wei Edgeworth expansion of random weighting estimation in semi-parametric regression models. (Chinese. English summary) Zbl 1073.62039 J. Lanzhou Univ. Technol. 31, No. 4, 120-123 (2005). Summary: In order to avoid the compulsory resampling bootstrap method when parameter estimation is performed in a simple semiparametric regression model \(y=x\beta+g(t)+\varepsilon\), a least squares random weighting estimation quantity \(\widetilde\lambda_n\) concerned with the parameter \(\beta\) was constructed by using a random weighting method. The Edgeworth expansion of the \(\widetilde \lambda_n\) distribution was obtained with convergence speed of order of \(O(n^{-1/2})\). MSC: 62G08 Nonparametric regression and quantile regression 62E20 Asymptotic distribution theory in statistics Keywords:rate of convergence; random weighting method PDFBibTeX XMLCite \textit{Z. Ren} et al., J. Lanzhou Univ. Technol. 31, No. 4, 120--123 (2005; Zbl 1073.62039)